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Machine Learning Defense Jobs in Texas (NOW HIRING)

9 Mothers

Machine Learning Engineer, Senior

Austin, TX · On-site

$103K - $142K/yr

Job Summary : 9 Mothers Defense develops AI-enabled systems to counter unmanned aerial threats. The company is seeking a Senior Machine Learning Engineer to design, train, and maintain models for ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer II to contribute to the development and ... defense applications. • Document designs, workflows, and operational best practices to ensure ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer II to contribute to the development and ... defense applications. • Document designs, workflows, and operational best practices to ensure ...

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Machine Learning Defense information

What are the key skills and qualifications needed to thrive as a Machine Learning Defense professional, and why are they important?

To thrive as a Machine Learning Defense professional, you need a strong background in computer science, cybersecurity, and machine learning, often supported by degrees in these fields or related certifications. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial machine learning techniques, and knowledge of security protocols are typically required. Critical thinking, problem-solving, and strong communication skills are essential for anticipating threats and collaborating with interdisciplinary teams. These skills ensure that AI systems remain robust and secure against evolving cyber threats, protecting sensitive data and organizational integrity.

What is machine learning defense?

Machine learning defense refers to techniques and strategies designed to protect machine learning models from various security threats, such as adversarial attacks, data poisoning, and model theft. These defenses can include methods like adversarial training, input sanitization, and robust model architectures. The goal is to ensure that machine learning systems remain accurate, reliable, and safe even when faced with malicious attempts to manipulate or exploit them. As machine learning becomes more widely adopted, the importance of effective defenses continues to grow.

What are some common challenges faced by professionals in Machine Learning Defense roles, and how can they be addressed?

Professionals in Machine Learning Defense often encounter challenges such as staying ahead of adversarial attacks, managing model robustness, and keeping up with rapidly evolving threat landscapes. Addressing these challenges typically requires continuous learning, collaboration with cybersecurity and data science teams, and implementing rigorous testing and monitoring frameworks for deployed models. Proactively participating in industry forums and staying updated on the latest research also help in identifying emerging threats and mitigation strategies.
What are popular job titles related to Machine Learning Defense jobs in Texas? For Machine Learning Defense jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Defense jobs in Texas look for? The top searched job categories for Machine Learning Defense jobs in Texas are:
What cities in Texas are hiring for Machine Learning Defense jobs? Cities in Texas with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you

Machine Learning Engineer, Senior

9 Mothers

Austin, TX • On-site

$103K - $142K/yr

Full-time

Re-posted 17 days ago

Job description

Job Summary:
9 Mothers Defense develops AI-enabled systems to counter unmanned aerial threats. The company is seeking a Senior Machine Learning Engineer to design, train, and maintain models for their counter-sUAS perception stack, focusing on model research and dataset engineering.
Responsibilities:
• Design, train, and iterate on machine learning models for detection, classification, and tracking of aerial targets.
• Own the dataset pipeline end-to-end, including data collection, labeling, curation, augmentation, synthetic data generation, and closed-loop retraining based on field performance.
• Build and maintain training infrastructure, including experiment tracking, compute orchestration, and evaluation harnesses.
• Define metrics and evaluation methodologies that correlate to real-world operational performance.
• Support deployment of trained models into the production perception stack, and address discrepancies between training and deployed performance.
• Analyze field data to identify and address model failure modes.
Qualifications:
Required:
• Demonstrated experience shipping machine learning systems into production under real-world operational requirements.
• Fluency in PyTorch or JAX, including full training loop development beyond fine-tuning off-the-shelf models.
• Strong software engineering skills beyond model development, including ownership of training infrastructure.
• Proficiency in Python; working knowledge of C++ or Rust at the training-to-deployment boundary.
• U.S. citizenship and ability to pass a background check.
Preferred:
• Experience with detection or tracking of small, fast, or adversarially perturbed targets.
• Synthetic data generation and sim-to-real methodologies.
• Experience training models for edge deployment, including quantization-aware training and knowledge distillation.
• Prior experience in defense or other safety-critical machine learning applications.
• Active security clearance, or eligibility to obtain one.
• Passion for building robots or engineering projects as a hobby
Company:
9 Mothers is a defense tech company that offers an AI-powered C-sUAS point defense turret designed to engage multiple fast-moving drones. Founded in 2024, the company is headquartered in Austin, USA, with a team of 11-50 employees. The company is currently Early Stage.

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